Oh how hard can it be

Funny, I'm falling into my own how-hard-can-it-be convex hull trap I described just three posts ago! It turns out my idea for a support mapping-based convex hull generator isn't that great after all. It works perfectly in 2D, but in 3D it turns out the surface can get concave during the process, which of course will mess up the whole thing, so just forget everything I ever said about convex hull now would you (except perhaps the part about it always being harder than you think)? Thanks. Back to the drawing board. There must be some way to compute convex hulls using only the support direction..

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Bokeh depth of field in a single pass

When I implemented bokeh depth of field I stumbled upon a neat blending trick almost by accident. In my opinion, the quality of depth of field is more related to how objects of different depths blend together, rather than the blur itself. Sure, bokeh is nicer than gaussian, but if the blending is off the whole thing falls flat. There seems to be many different approaches to this out there, most of them requiring multiple passes and sometimes separation of what's behind and in front of the focal plane. I experimented a bit and stumbled upon a nice trick, almost by accident. I'm not going to get into technical details about lenses, circle of confusion, etc. It has been described very well many times before, so I'm just going to assume you know the basics. I can try to summarize what we want to do in one sentence – render each pixel as a discs where the radius is determined by how out of focus it is, also taking depth into consideration "somehow". Taking depth i

Screen Space Path Tracing – Diffuse

The last few posts has been about my new screen space renderer. Apart from a few details I haven't really described how it works, so here we go. I split up the entire pipeline into diffuse and specular light. This post will focusing on diffuse light, which is the hard part. My method is very similar to SSAO, but instead of doing a number of samples on the hemisphere at a fixed distance, I raymarch every sample against the depth buffer. Note that the depth buffer is not a regular, single value depth buffer, but each pixel contains front and back face depth for the first and second layer of geometry, as described in this post . The increment for each step is not view dependant, but fixed in world space, otherwise shadows would move with the camera. I start with a small step and then increase the step exponentially until I reach a maximum distance, at which the ray is considered a miss. Needless to say, raymarching multiple samples for every pixel is very costly, and this is with

Sprinkle behind the scenes

This summer me and a friend released a physics puzzler for iOS and Android based on fluid simulation. It started as a really small project almost a year ago, but grew along the way and has been really well received on both platforms. Last year i posted movie clips from a fluid simulator I was working on, and the fluid in Sprinkle is basically the same algorithm, but in 2D and with lots of optimizations. The simulator is particle-based, but not traditional SPH. Instead, the pressure and velocity is solved with a regular "sequential impulse"-solver. It's quite a mindjob to work out the constraint formulation, but it's worth the effort, since you get unconditionally stable fluid that is reasonably fast and interacts seamlessly with rigid bodies. The most compoutationally intensive operation is neighbor finding. I'm using a pretty standard spatial hashing technique, with a twist. Each particle gets assigned which quadrant within the cell it belongs to, and a

Mediocre game technology

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